Google’s Chatbot: Almost Perfect 🤖

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Google’s Chatbot: Almost Perfect 🤖

Two Minute Papers 21.03.2020 253 649 просмотров 9 067 лайков

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Анализ с AI

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❤️ Check out Lambda here and sign up for their GPU Cloud: https://lambdalabs.com/papers 📝 The paper "Towards a Human-like Open-Domain Chatbot" is available here: https://arxiv.org/abs/2001.09977 ❤️ Watch these videos in early access on our Patreon page or join us here on YouTube: - https://www.patreon.com/TwoMinutePapers - https://www.youtube.com/channel/UCbfYPyITQ-7l4upoX8nvctg/join 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Alex Haro, Alex Paden, Andrew Melnychuk, Angelos Evripiotis, Anthony Vdovitchenko, Benji Rabhan, Brian Gilman, Bryan Learn, Daniel Hasegan, Dan Kennedy, Dennis Abts, Eric Haddad, Eric Martel, Evan Breznyik, Geronimo Moralez, James Watt, Javier Bustamante, Kaiesh Vohra, Kasia Hayden, Kjartan Olason, Levente Szabo, Lorin Atzberger, Lukas Biewald, Marcin Dukaczewski, Marten Rauschenberg, Maurits van Mastrigt, Michael Albrecht, Michael Jensen, Nader Shakerin, Owen Campbell-Moore, Owen Skarpness, Raul Araújo da Silva, Rob Rowe, Robin Graham, Ryan Monsurate, Shawn Azman, Steef, Steve Messina, Sunil Kim, Taras Bobrovytsky, Thomas Krcmar, Torsten Reil, Tybie Fitzhugh. https://www.patreon.com/TwoMinutePapers Meet and discuss your ideas with other Fellow Scholars on the Two Minute Papers Discord: https://discordapp.com/invite/hbcTJu2 Károly Zsolnai-Fehér's links: Instagram: https://www.instagram.com/twominutepapers/ Twitter: https://twitter.com/karoly_zsolnai Web: https://cg.tuwien.ac.at/~zsolnai/

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Introduction

dear fellow scholars this is two minute papers with dr. Khurana if I here when I was growing up IQ tests were created by humans to test the intelligence of other humans if someone told me just 10 years ago that algorithm will create IQ tests to be taken by other algorithms I wouldn't have believed a word of it yet just a year ago scientists at deep mind created a program that is able to generate a large amount of problems that test abstract reasoning capabilities they are inspired by human IQ tests with all these questions about sizes colors and progressions they wrote their own neural network to take these tests which performed remarkably well how well exactly in the presence of nasty distractor objects it was able to find out the correct solution about 62% of the time and if we remove these distractors which i will note that are good at misdirecting humans too the AI was correct 78% of the time awesome but today we are capable of writing even more sophisticated learning algorithms that can even complete our sentences not

What is GPT2

so long ago the open AI lab published GPT 2 a technique that they unleashed to read the internet and it learned our language by itself a few episodes ago we gave it a spin and I almost fell out of the chair when I saw that it could finish my sentences about fluid simulations in such a scholarly way that I think could easily fool a layperson have a look here and judge for yourself this GPT 2 technique was a neural network variant that was trained using one and a half billion parameters at the risk of oversimplifying what that means it roughly refers to the internal complexity of the networks or in other words how many weights and connections are there and now the Google brain team has released Mena an open domain chat bot that uses 2. 6 billion parameters and shows remarkable human-like properties the chat bot part means piece of software or a machine that we can talk to and the open domain part refers to the fact that we can try any topic hotels movies the ocean favorite movie characters or pretty much anything we can think of and expect a bot to do well so how do we know that it's really good well let's try to evaluate it in two different ways first let's try the super fun but less scientific way or in other words what we are already doing looking at chat logs you see Meanor writing on the left and a

Jokes

human being on the right and it not only answers questions sensibly and coherently but is even capable of cracking a joke of course if you consider a pan to be a joke that is you see a selection of topics here where

Philosophy

the user talks with Mina about movies and the bot expresses the desire to see the grand budapest hotel which is indeed a very human-like quality it can also try to come up with a proper definition of philosophy and now since we are scholars we would also like to measure how human-like this is in a more scientific manner as well now is a good time to hold on to your papers because

Science

this is measured by the sensibleness and specificity average scored from now on SSA in short in which humans are here previous chatbots are down there and Mina is right there close by which means that it is easy to be confused for a real human that already sounds like science fiction however let's be a little nosy here and also ask how do we know if this SSA is any good in predicting what is human-like and what isn't excellent question when measuring human likeness for these chatbots plugging in the SSA again the sensibleness and specificity average we see that they correlate really strongly which means that the two seem to measure very similar things and in this case SSA can indeed be used as a proxy for human likeness the coefficient of determination is 0. 9 t6 this is a several times stronger correlation than we can measure between the intelligence and the grades of a student which is already a great correlation this is a remarkable result now what we get out of

Conclusion

this is that the SSA is much easier and precise to measure than human likeness and his hands used throughout the paper so chatbot say what are all these things useful for well do you remember Google's technique that would automatically use an AI to talk to your colors and screen your course or even make calls on your behalf when connected to a text-to-speech synthesizer something that Google already does amazingly well Mina could really come alive in our daily lives soon what a time to be alive

Outro

this episode has been supported by Lamba if you're a researcher or a startup looking for cheap GPU compute to run these algorithms check out lambda GPU cloud I've talked about lambdas GPU workstations in other videos and I'm happy to tell you that they are offering GPU cloud services as well the lambda GPU cloud can train imagenet to 93% accuracy for less than $19 lambdas web-based IDE lets you easily access your instance right in your browser and finally hold on to your papers because the lambda GPU cloud costs less than half of AWS and aja make sure to go to lambda lab dot-com / papers and sign up for one of their amazing GPU instances today our thanks to lambda for helping us make better videos for you thanks for watching and for your generous support and I'll see you next time

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